






import operator as op


__UpperCamelCase   :   int      =    """scaler.pt"""
__UpperCamelCase   :   int      =    """pytorch_model"""
__UpperCamelCase   :   Union[str, Any]      =    """random_states"""
__UpperCamelCase   :   Any      =    """optimizer"""
__UpperCamelCase   :   Tuple      =    """scheduler"""
__UpperCamelCase   :   List[Any]      =    """pytorch_model.bin"""
__UpperCamelCase   :   Union[str, Any]      =    """pytorch_model.bin.index.json"""
__UpperCamelCase   :   List[str]      =    """model.safetensors"""
__UpperCamelCase   :   str      =    """model.safetensors.index.json"""
__UpperCamelCase   :   Dict      =    """1.10.2"""
__UpperCamelCase   :   Any      =    """py38"""
__UpperCamelCase   :   Union[str, Any]      =    """4.17.0"""
__UpperCamelCase   :   Optional[Any]      =    ["""ml.p3.16xlarge""", """ml.p3dn.24xlarge""", """ml.p4dn.24xlarge"""]
__UpperCamelCase   :   Tuple      =    ["""FULL_SHARD""", """SHARD_GRAD_OP""", """NO_SHARD""", """HYBRID_SHARD""", """HYBRID_SHARD_ZERO2"""]
__UpperCamelCase   :   List[Any]      =    ["""TRANSFORMER_BASED_WRAP""", """SIZE_BASED_WRAP""", """NO_WRAP"""]
__UpperCamelCase   :   str      =    ["""BACKWARD_PRE""", """BACKWARD_POST""", """NO_PREFETCH"""]
__UpperCamelCase   :   Optional[int]      =    ["""FULL_STATE_DICT""", """LOCAL_STATE_DICT""", """SHARDED_STATE_DICT"""]
__UpperCamelCase   :   int      =    """2.0.1"""
__UpperCamelCase   :   Optional[int]      =    ["""pdsh""", """standard""", """openmpi""", """mvapich"""]
__UpperCamelCase   :   Union[str, Any]      =    ["""default""", """reduce-overhead""", """max-autotune"""]

__UpperCamelCase   :   str      =    {""">""": op.gt, """>=""": op.ge, """==""": op.eq, """!=""": op.ne, """<=""": op.le, """<""": op.lt}

# These are the args for `torch.distributed.launch` for pytorch < 1.9
__UpperCamelCase   :   Dict      =    [
    """nnodes""",
    """nproc_per_node""",
    """rdzv_backend""",
    """rdzv_endpoint""",
    """rdzv_id""",
    """rdzv_conf""",
    """standalone""",
    """max_restarts""",
    """monitor_interval""",
    """start_method""",
    """role""",
    """module""",
    """m""",
    """no_python""",
    """run_path""",
    """log_dir""",
    """r""",
    """redirects""",
    """t""",
    """tee""",
    """node_rank""",
    """master_addr""",
    """master_port""",
]

__UpperCamelCase   :   List[str]      =    ["""DEEPSPEED""", """MULTI_GPU""", """FSDP""", """MEGATRON_LM"""]
__UpperCamelCase   :   Tuple      =    ["""DEEPSPEED""", """MULTI_XPU""", """FSDP"""]








'''simple docstring'''






from __future__ import annotations

lowerCAmelCase									=   []






def   __A    (				a_    :	list[list[int]]   ,a_    :	int   ,a_    :	int						):
		for i in range(len(a_						)						):
				if board[row][i] == 1:
						return False
		for i in range(len(a_						)						):
				if board[i][column] == 1:
						return False
		for i, j in zip(range(a_   ,-1   ,-1						)   ,range(a_   ,-1   ,-1						)						):
				if board[i][j] == 1:
						return False
		for i, j in zip(range(a_   ,-1   ,-1						)   ,range(a_   ,len(a_						)						)						):
				if board[i][j] == 1:
						return False
		return True






def   __A    (				a_    :	list[list[int]]   ,a_    :	int						):
		if row >= len(a_						):
				solution.append(a_						)
				printboard(a_						)
				print()
				return True
		for i in range(len(a_						)						):
				if is_safe(a_   ,a_   ,a_						):
						lowerCAmelCase  :     Dict       						= 1
						solve(a_   ,row + 1						)
						lowerCAmelCase  :     Optional[int]       						= 0
		return False






def   __A    (				a_    :	list[list[int]]						):
		for i in range(len(a_						)						):
				for j in range(len(a_						)						):
						if board[i][j] == 1:
								print("Q"   ,end=" "						)
						else:
								print("."   ,end=" "						)
				print()


# n=int(input("The no. of queens"))
lowerCAmelCase									=   8
lowerCAmelCase									=   [[0 for i in range(n)] for j in range(n)]
solve(board, 0)

print("""The total no. of solutions are :""", len(solution))



